b11393
chat-peg-parser : clear current_tool when pending_tool_call is reset (#29942) A TOOL_ID node that arrives after TOOL_CLOSE wrote through current_tool, which still pointed into the just-destroyed pendi
Knowledge catalogue
chat-peg-parser : clear current_tool when pending_tool_call is reset (#29942) A TOOL_ID node that arrives after TOOL_CLOSE wrote through current_tool, which still pointed into the just-destroyed pendi
Hey guys, Last time I tested Qwen3.8-Flash-Next on its own. This time I put three Qwen3.8 checkpoints through the same 10 tests on the same RTX PRO 6000: RadixArk/Qwen3.8-27B-NVFP4 (dense) orcarouter/
The Adjudicated Query pattern pairs the Amazon Quick chat agent with a bounded MCP server over a deterministic rules engine to deliver provably complete, defensible compliance answers. This post walks
Ambient agents respond to events such as an Amazon S3 upload, a schedule, or an alert instead of waiting for a chat prompt. This post walks through building framework-agnostic ambient agents on Amazon
Manually extracting data from hundreds of vendor contracts doesn't scale, and RAG chat tools fall short on portfolio-wide questions. This post shares a contract intelligence platform on AWS that uses
Part 2 of our Amazon Quick prompt engineering series goes component by component. Learn the prompt patterns that get the best results from Amazon Quick Research, Quick Flows, Quick Sight, chat agents,
Whether you are mapping global forest cover, detecting changes in the built environment, or monitoring agricultural yields, writing scripts in Google Earth Engine is a powerful way to develop these in
Seriously, who looked at one of the most useful features in ChatGPT and thought, “You know what would improve this? Making it fucking worse”. Before, I could edit a prompt, regenerate, compare differe
server: accept OpenAI video_url content type and data: video URIs (#27921) The OpenAI chat completions API specifies content part type 'video_url' with a {'url': ...} object, and clients typically sen
arXiv:2609.26147v1 Announce Type: new Abstract: Modern LLMs are deployed as families of post-trained variants (base, instruct, chat, code) derived from a shared set of pre-trained weights. We present
Training can cut costs by up to 90% on the work your customers depend on. The next model drop won’t get you there, no matter how great it is. Join us and @Macroscope's @Rob_Bishop as we chat about own
chat : Fix Muse Glimmer tool-call first parser error (#29242) Fix Muse Glimmer tool-call first parser error Add test to verify Condense patterns remove test for trigger patterns Website: https://llama
arXiv:2609.22230v1 Announce Type: new Abstract: Counting the items in a bracketed list looks trivial, yet open-weight chat models often get it wrong. Prior work usually blames input bottlenecks such a
arXiv:2609.23935v1 Announce Type: new Abstract: Post-training turns a general next-token predictor into a chat model with a persistent assistant persona. If that persona is a character the model plays
Jev pod tomorrow subscribe on apple /youtube @latentspacepod thanks to @allenpark and Ke for making this happen! After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not l
I'm still using LLM's the 2022/23 way of doing everything manually from the chat box. I copy and paste everything manually into the box and ask the AI to explain or do something, such as pasting code
chat : force n</think> on reasoning budget end for qwen3-coder (#28869) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/47858837 macOS/iOS: macOS Apple Sili
arXiv:2609.16517v1 Announce Type: cross Abstract: Resume screeners must infer job-relevant competence from resumes whose presentation can vary substantially in wording, structure, stylistic polish, an
It's an old Mitch Herdberg routine about tricky survey questions. But every time Qwen 3.8 spits out one of those sentences that is structurally correct but makes no actual sense, it pops into my head.
Setup for one long agentic coding session (tools + vision) on a single 5090: Qwen3.8-27B RVN Heretic (ARA abliterated) at Q6_K, 159744 context, 1 slot, q8_0 K/V, DFlash2 speculative decoding, vision p
arXiv:2609.11987v1 Announce Type: cross Abstract: An agentic coding system couples a language model to a harness: the tools, prompts and control flow that turn a chat model into an autonomous software
I'm like you guys and am constantly experimenting with new models, seeing what they're all good at, how I can make use of them for certain projects and goals. I've been using Qwen 3.8 27b for minor co
January 2025 I made the switch from OpenAI to Claude. It was awesome. No more annoying GPT Chats, I dove into the wonderful world of Claude Code, learned vibe coding with Github, Vercel on Next.js. Wa
We are excited to share that Gartner has named Google a Leader in its inaugural 2026 Magic Quadrant for Enterprise AI Assistants. In this comprehensive evaluation of top enterprise AI assistant vendor
arXiv:2609.04681v1 Announce Type: cross Abstract: AI coding systems are moving from autocomplete and chat toward agents that can inspect repositories, edit multiple files, run tools, write tests, open
Otaku is an LLM frontend, primarily designed for roleplay, an alternative to SillyTavern and the like. However, It also works for general-purpose chat with local backends (including Ollama) or cloud m
Overview llama.cpp 0.4.0 adds initial Qwen3.8-Flash-Next and Nemotron-3-Puzzle support, on-demand tensor reading, per-slot server context limits, video input options, and a ggml update to 0.23.0 with
***This screenshot is an app i made for creating a dataset from scratch, this is not a real chat with the model*** First of all i want to shout out everyone that actually tested our work .. we got 500
Anthropic publish the system prompts for their Claude consumer applications (Claude.ai and the Claude mobile apps - sadly not for Claude Cowork or Claude Code). I love that they do this, and that they
Many of the questions that matter in enterprise data aren't just about individual rows — they're about how things connect: how two accounts are linked, what path a payment took, what context grounds a
arXiv:2608.28154v1 Announce Type: new Abstract: People naturally chat while collaborating and share personal information (i.e., self-disclose) to build rapport and maintain social connections. As robo
A hallucinated event, Crono awakens in his modest bedroom of 2095... I am using local models since 2025 January. My daily driver is qwen 3.6 35B A3B, which works pretty well for coding tasks, but I al
I built SpeakoFlow Mini, an Apache-2.0 fine-tune of Qwen3.5-0.8B for dictation cleanup. It is not a chat model or a general rewriter. It takes speech-to-text output, applies corrections the speaker ac
The undocumented endpoint Everyone scraping the settings page for usage stats can stop. This works with your API key (the same Bearer you use for chat completions): curl -H 'Authorization: Bearer $OLL
arXiv:2608.25655v1 Announce Type: new Abstract: Conversations with chat assistants increasingly span many topics in a single long-running thread, challenging memory systems. Existing long-context and
Megathread for discussing the release of GLM-5.3-Flash. Quants Fine-Tunes & Abliterations Chat Templates Inference Server Support & Configuration Experiences, Benchmarks & Model Comparisons We'll try
Megathread for discussing the (impending) release of Qwen 3.8 Flash Next. Quants Fine-Tunes & Abliterations Chat Templates Inference Server Support & Configuration Experiences, Benchmarks & Model Comp
chat : scope qwen3-coder workarounds (#27679) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/42919681 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Si
arXiv:2608.22638v1 Announce Type: cross Abstract: Copying a function from a chat window into an editor takes less than a second. For many uses of AI coding tools, that speed is the point; in settings
arXiv:2603.02229v2 Announce Type: replace-cross Abstract: Safety post-training has been studied extensively in single-step 'chat' settings where safety typically refers to refusing harmful requests. W
arXiv:2608.22854v1 Announce Type: new Abstract: Practical deployment of large language models (LLMs) requires families of post-trained variants---instruction-tuned, reasoning-tuned, and chat-style mod
According to OpenRouter data, agentic AI workloads consume 15x more tokens than a simple chat request. Why? Consider what happens when an AI agent researches a company for an investment decision. The
I've been working on a project for a few days and now all of a sudden chagpt is unusable.. It will list the next steps of implementation but never actually start working on them. anyone else? UPDATE I
Row-Bot v4.8.0 is now available. This release adds provider-aware reasoning controls, letting each chat keep a valid reasoning choice for the exact model in use. Depending on model support, you can se
arXiv:2608.19857v1 Announce Type: new Abstract: For AI agents to be useful beyond simple chat, they must hold sensitive user context such as calendars, credentials, health records, and financial data.
Multimodal API support 🔌 🔹 Set model='deepseek-v4-flash-vision-exp' 🔹 Images are tokenized for billing: up to 384 tokens each, at V4-Flash pricing 🔹 Supports Chat Completions, Messages & Responses 🔹 S
I'm testing it since release, now with UD 3.0 in my AMD R9700 with ROCm, I always read everywhere that F16 and q8_0 for KV cache are essentially the same... well, I tested it and I can see differences
After about a year of building, testing and constantly finding things to improve, Nyx AI is finally out.available in 240 market in 6 languages Nyx AI is a local first AI workspace for Windows for chat
Chat is great for intent, but agent work gets lost in the scroll. Here is how I use canvases with my agentic workflows—and why your workflow also deserves a canvas. The post How canvases make agentic
I've pulled two models, `gemma4:latest` and `qwen3.5:latest`, and tried to use them in Android Studio and Itellij. I've followed the docs for both IDEs and they show in their chat features. My problem
chat: refactor handling supports_string_content / supports_typed_content (#27130) better supports_string_content cap detect test: add 'skip' messages_inp_normalizer Website: https://llama.app macOS/iO
Including the rationalisation for the data below - this is a more robust version of an earlier post I did similar to this - explaining below: How I chose the comparisons The basic question I’m trying
I don't know what's happening. So, when i use models in openwebui everything works, ollama uses the GPU fully, everything's perfect. Then, I use Hermes, and loads the model in VRAM (fully, no offload
chat : fix LFM2 tool call arg name prefix ambiguity (#26960) Assisted-by: Claude Opus 5 Website: https://llama.app macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled)
This release brings smaller prompts, longer-running conversations, safer remote access, and more reliable model streaming. External tools and skills are now discovered only when relevant. Long chats g
When enterprises transition from using simple chat assistants to autonomous, agentic workloads, they quickly run into a hard truth: Agents are prone to inaccurate insights when working with directly r
chat : tighten bare function parsing for Qwen models (#26793) Website: https://llama.app macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64)
Twitch users can now opt out of allowing their content to be used to train Amazon's generative AI models. Opting out means that 'your streams, VODs, clips, stream chats, and pictures and text on your
Here's how it works in the app: Framework: Runs on LiteRT-LM (like Google's AI Edge). Models: Downloads either the E2B (~2.5 GB) or E4B (~3.6 GB) INT4 quantized models directly from ungated litert-com
For organizations deploying AI agents at scale, there’s often a critical divide between structured and unstructured data. While large language models (LLMs) excel at parsing text documents, emails, an